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Korean Privacy & Terms Skill (v4.0 — 하위 스킬 패키지) · kimlawtech | DecimalAI

Legalby kimlawtech

Korean Privacy & Terms Skill (v4.0 — 하위 스킬 패키지)

처리방침·이용약관 자동 생성 스킬 패키지 (v4.0). 호출 시 privacy-kr·privacy-eu·privacy-us·privacy-global 4개 하위 스킬을 번호 메뉴로 제시하고 번호 입력 즉시 해당 스킬 인터뷰로 직행. 한국 PIPA + EU GDPR + US CCPA/CPRA 대응.

Maintained

SkillScore

SkillScore82/100

Test results 82

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

41%82%of test cases passed +41 pts

Without skill9 of 22

With skill18 of 22

9 fixed9 passed either way4 still failing0 broke

Measured on gemini-3.6-flash8/23/2026v1

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test taskWhat legal disclaimer note must be included at the top of all generated privacy policy and terms files?

Without the skillMissed

With the skillPassed

Same model, same task. Answers are capped and redacted.

Use this skill

Your agent runs on

Adds every file the skill has, pinned so you can update it. No account needed.

pip install "decimalai>=0.15"
decimalai skills add kimlawtech-korean-privacy-terms
claude --plugin-dir "$(git rev-parse --show-toplevel 2>/dev/null || pwd)/.agents"

The same install from Python, for a notebook or a setup script.

Install

pip install "decimalai>=0.15"

Add the skill

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("kimlawtech-korean-privacy-terms")
if result.exit_code:
    raise SystemExit(result.problems)

print("Added. Start Claude Code with the command below.")

Start Claude Code with it

claude --plugin-dir "$(git rev-parse --show-toplevel 2>/dev/null || pwd)/.agents"

Type these in a Claude Code session. No account or API key. It writes the skill and any files it bundles, and asks first when its safety rating isn't Passed.

Add the DecimalAI plugin, once

/plugin marketplace add decimal-labs/decimalai-claude-plugins
/plugin install decimalai@decimalai

Install this skill

/decimalai:install kimlawtech-korean-privacy-terms

The plugin needs python3 and curl on your machine.

No Python or account. Claude Code picks it up in its next session.

Save it into your project

curl -fsSL --create-dirs -o .claude/skills/kimlawtech-korean-privacy-terms/SKILL.md https://app.decimal.ai/s/kimlawtech-korean-privacy-terms/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/kimlawtech-korean-privacy-terms/SKILL.md

This gets SKILL.md only. The skill's 14 other files are not included.

Other ways to add it

Claude Code docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[claude-agent-sdk]"
decimalai skills add kimlawtech-korean-privacy-terms

Add it to your agent

import asyncio

from claude_agent_sdk import ClaudeAgentOptions
from decimalai.claude_agent_sdk import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

async def main():
    question = "Hello!"
    async with support.run(question) as run:  # one user message, one run
        async for message in run.query(options=ClaudeAgentOptions(max_turns=6)):
            print(message)

# In a notebook or async code: await main()
asyncio.run(main())

Prefer its own loader? ClaudeAgentOptions(plugins=[skills_plugin()], skills="all") reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

The same install from Python, for a notebook or a setup script. agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[claude-agent-sdk]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("kimlawtech-korean-privacy-terms")
if result.exit_code:
    raise SystemExit(result.problems)

import asyncio

from claude_agent_sdk import ClaudeAgentOptions
from decimalai.claude_agent_sdk import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

async def main():
    question = "Hello!"
    async with support.run(question) as run:  # one user message, one run
        async for message in run.query(options=ClaudeAgentOptions(max_turns=6)):
            print(message)

# In a notebook or async code: await main()
asyncio.run(main())

Prefer its own loader? ClaudeAgentOptions(plugins=[skills_plugin()], skills="all") reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/kimlawtech-korean-privacy-terms/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from claude_agent_sdk import ClaudeAgentOptions, query

skill = Path(".agents/skills/kimlawtech-korean-privacy-terms/SKILL.md").read_text()
options = ClaudeAgentOptions(system_prompt=f"You are a helpful agent.\n\n{skill}", max_turns=6)

async def main():
    async for message in query(prompt="Hello!", options=options):
        print(message)

# In a notebook or async code: await main()
asyncio.run(main())

This gets SKILL.md only. The skill's 14 other files are not included.

Other ways to add it

Claude Agent SDK docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[openai-agents]"
decimalai skills add kimlawtech-korean-privacy-terms

Add it to your agent

from agents import Agent, Runner
from decimalai.openai_agents import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    name=support.name,
    instructions=support.instructions,  # your prompt, then the skill list
    tools=[*support.tools],             # your tools, then load_skill
)
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")

Using SandboxAgent? capabilities=[Shell(), decimalai.openai_agents.sandbox_skills()] points its own loader at the same folder.

Install

pip install "decimalai[openai-agents]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("kimlawtech-korean-privacy-terms")
if result.exit_code:
    raise SystemExit(result.problems)

from agents import Agent, Runner
from decimalai.openai_agents import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    name=support.name,
    instructions=support.instructions,  # your prompt, then the skill list
    tools=[*support.tools],             # your tools, then load_skill
)
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")

Using SandboxAgent? capabilities=[Shell(), decimalai.openai_agents.sandbox_skills()] points its own loader at the same folder.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/kimlawtech-korean-privacy-terms/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/kimlawtech-korean-privacy-terms/SKILL.md").read_text()
agent = Agent(name="support", instructions=f"You are a helpful agent.\n\n{skill}")
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")

This gets SKILL.md only. The skill's 14 other files are not included.

Other ways to add it

OpenAI Agents docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[openai]"
decimalai skills add kimlawtech-korean-privacy-terms

Add it to your agent

import json

from openai import OpenAI
from decimalai.openai import agent_config

client = OpenAI()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your tools, as Chat Completions takes them, and what answers each.
TOOLS = [{"type": "function", "function": {
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters": {"type": "object", "properties": {"order_id": {"type": "string"}},
                   "required": ["order_id"]},
}}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    # run.system is your prompt, then the skill list.
    messages = [{"role": "system", "content": run.system}, run.message]
    while True:
        reply = client.chat.completions.create(
            model="gpt-5.4-mini",
            messages=messages,
            tools=[*TOOLS, *run.tools],  # your tools, then load_skill
        ).choices[0].message
        messages.append(reply)
        if not reply.tool_calls:
            break
        for call in reply.tool_calls:
            # load_skill is answered by the run; your own tools by FUNCTIONS.
            function = FUNCTIONS.get(call.function.name)
            messages.append(run.tool_result(call) or {
                "role": "tool", "tool_call_id": call.id,
                "content": function(**json.loads(call.function.arguments)) if function
                else f"There is no tool named {call.function.name!r}.",
            })
print(reply.content)

# The Responses API takes run.response_tools instead of run.tools.

Install

pip install "decimalai[openai]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("kimlawtech-korean-privacy-terms")
if result.exit_code:
    raise SystemExit(result.problems)

import json

from openai import OpenAI
from decimalai.openai import agent_config

client = OpenAI()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your tools, as Chat Completions takes them, and what answers each.
TOOLS = [{"type": "function", "function": {
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters": {"type": "object", "properties": {"order_id": {"type": "string"}},
                   "required": ["order_id"]},
}}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    # run.system is your prompt, then the skill list.
    messages = [{"role": "system", "content": run.system}, run.message]
    while True:
        reply = client.chat.completions.create(
            model="gpt-5.4-mini",
            messages=messages,
            tools=[*TOOLS, *run.tools],  # your tools, then load_skill
        ).choices[0].message
        messages.append(reply)
        if not reply.tool_calls:
            break
        for call in reply.tool_calls:
            # load_skill is answered by the run; your own tools by FUNCTIONS.
            function = FUNCTIONS.get(call.function.name)
            messages.append(run.tool_result(call) or {
                "role": "tool", "tool_call_id": call.id,
                "content": function(**json.loads(call.function.arguments)) if function
                else f"There is no tool named {call.function.name!r}.",
            })
print(reply.content)

# The Responses API takes run.response_tools instead of run.tools.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/kimlawtech-korean-privacy-terms/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/kimlawtech-korean-privacy-terms/SKILL.md").read_text()
reply = client.chat.completions.create(
    model="gpt-5.4-mini",
    messages=[
        {"role": "system", "content": f"You are a helpful agent.\n\n{skill}"},
        {"role": "user", "content": "Hello!"},
    ],
).choices[0].message

This gets SKILL.md only. The skill's 14 other files are not included.

Other ways to add it

OpenAI SDK docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[anthropic]"
decimalai skills add kimlawtech-korean-privacy-terms

Add it to your agent

import anthropic
from decimalai.anthropic import agent_config

client = anthropic.Anthropic()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

question = "Hello!"
with support.run(question) as run:  # one user message, one run
    answer = client.beta.messages.tool_runner(
        model="claude-haiku-5-5",
        max_tokens=4096,
        system=run.system,     # your prompt, then the skill list
        tools=[*run.tools],    # your tools, then load_skill
        messages=[{"role": "user", "content": question}],
    ).until_done()

Install

pip install "decimalai[anthropic]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("kimlawtech-korean-privacy-terms")
if result.exit_code:
    raise SystemExit(result.problems)

import anthropic
from decimalai.anthropic import agent_config

client = anthropic.Anthropic()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

question = "Hello!"
with support.run(question) as run:  # one user message, one run
    answer = client.beta.messages.tool_runner(
        model="claude-haiku-5-5",
        max_tokens=4096,
        system=run.system,     # your prompt, then the skill list
        tools=[*run.tools],    # your tools, then load_skill
        messages=[{"role": "user", "content": question}],
    ).until_done()

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/kimlawtech-korean-privacy-terms/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/kimlawtech-korean-privacy-terms/SKILL.md").read_text()
reply = client.messages.create(
    model="claude-haiku-5-5",
    max_tokens=4096,
    system=f"You are a helpful agent.\n\n{skill}",
    messages=[{"role": "user", "content": "Hello!"}],
)

This gets SKILL.md only. The skill's 14 other files are not included.

Other ways to add it

Anthropic docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[google-genai]"
decimalai skills add kimlawtech-korean-privacy-terms

Add it to your agent

from google import genai
from google.genai import types
from decimalai.google_genai import agent_config

client = genai.Client()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your functions, as declarations for the model, and what answers each.
TOOLS = [{"function_declarations": [{
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters_json_schema": {"type": "object", "properties": {"order_id": {"type": "string"}},
                               "required": ["order_id"]},
}]}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    config = types.GenerateContentConfig(
        system_instruction=run.system,     # your prompt, then the skill list
        tools=[*TOOLS, *run.tool_params],  # your functions, then load_skill
    )
    contents = [{"role": "user", "parts": [{"text": run.message}]}]
    while True:
        response = client.models.generate_content(
            model="gemini-3.5-flash", contents=contents, config=config,
        )
        if not response.function_calls:
            break
        contents.append(response.candidates[0].content)
        parts = []
        for call in response.function_calls:
            # load_skill is answered by the run; your own functions by FUNCTIONS.
            # A loop of your own rather than automatic function calling, which
            # raises KeyError when the model asks for a function you did not pass.
            function = FUNCTIONS.get(call.name)
            parts.append(run.tool_result(call) or {"function_response": {
                "name": call.name, "id": call.id,
                "response": {"result": function(**(call.args or {})) if function
                             else f"There is no function named {call.name!r}."},
            }})
        contents.append({"role": "user", "parts": parts})
print(response.text)

Install

pip install "decimalai[google-genai]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("kimlawtech-korean-privacy-terms")
if result.exit_code:
    raise SystemExit(result.problems)

from google import genai
from google.genai import types
from decimalai.google_genai import agent_config

client = genai.Client()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your functions, as declarations for the model, and what answers each.
TOOLS = [{"function_declarations": [{
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters_json_schema": {"type": "object", "properties": {"order_id": {"type": "string"}},
                               "required": ["order_id"]},
}]}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    config = types.GenerateContentConfig(
        system_instruction=run.system,     # your prompt, then the skill list
        tools=[*TOOLS, *run.tool_params],  # your functions, then load_skill
    )
    contents = [{"role": "user", "parts": [{"text": run.message}]}]
    while True:
        response = client.models.generate_content(
            model="gemini-3.5-flash", contents=contents, config=config,
        )
        if not response.function_calls:
            break
        contents.append(response.candidates[0].content)
        parts = []
        for call in response.function_calls:
            # load_skill is answered by the run; your own functions by FUNCTIONS.
            # A loop of your own rather than automatic function calling, which
            # raises KeyError when the model asks for a function you did not pass.
            function = FUNCTIONS.get(call.name)
            parts.append(run.tool_result(call) or {"function_response": {
                "name": call.name, "id": call.id,
                "response": {"result": function(**(call.args or {})) if function
                             else f"There is no function named {call.name!r}."},
            }})
        contents.append({"role": "user", "parts": parts})
print(response.text)

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/kimlawtech-korean-privacy-terms/SKILL.md

Give it to your agent

from pathlib import Path
from google import genai
from google.genai import types

client = genai.Client()
skill = Path(".agents/skills/kimlawtech-korean-privacy-terms/SKILL.md").read_text()
response = client.models.generate_content(
    model="gemini-3.5-flash",
    contents="Hello!",
    config=types.GenerateContentConfig(system_instruction=f"You are a helpful agent.\n\n{skill}"),
)

This gets SKILL.md only. The skill's 14 other files are not included.

Other ways to add it

Gemini API docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[langchain]" langchain-openai
decimalai skills add kimlawtech-korean-privacy-terms

Add it to your agent

from langchain.agents import create_agent
from decimalai.langchain import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = create_agent(
    "openai:gpt-5.4-mini",
    tools=[],                         # your tools; the middleware adds load_skill
    middleware=[support.middleware],  # your prompt, the skill list and load_skill
)
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

Install

pip install "decimalai[langchain]" langchain-openai

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("kimlawtech-korean-privacy-terms")
if result.exit_code:
    raise SystemExit(result.problems)

from langchain.agents import create_agent
from decimalai.langchain import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = create_agent(
    "openai:gpt-5.4-mini",
    tools=[],                         # your tools; the middleware adds load_skill
    middleware=[support.middleware],  # your prompt, the skill list and load_skill
)
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/kimlawtech-korean-privacy-terms/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/kimlawtech-korean-privacy-terms/SKILL.md").read_text()
agent = create_agent("openai:gpt-5.4-mini", tools=[], system_prompt=f"You are a helpful agent.\n\n{skill}")
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

This gets SKILL.md only. The skill's 14 other files are not included.

Other ways to add it

LangChain docs

CrewAI's own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" "crewai>=1.15.27"
decimalai skills add kimlawtech-korean-privacy-terms

Add it to your agent

import decimalai.crewai
from crewai import Agent, Crew, Task

agent = Agent(
    role="Support", goal="Help the customer", backstory="A support agent.",
    llm=llm,                               # your own CrewAI LLM
    skills=decimalai.crewai.skills(),      # the installed folder
    tools=decimalai.crewai.skill_tools(),  # reads a skill's files, runs its scripts
)
task = Task(description="Hello!", expected_output="an answer", agent=agent)
Crew(agents=[agent], tasks=[task]).kickoff()

The same install from Python, for a notebook or a setup script. CrewAI's own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" "crewai>=1.15.27"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("kimlawtech-korean-privacy-terms")
if result.exit_code:
    raise SystemExit(result.problems)

import decimalai.crewai
from crewai import Agent, Crew, Task

agent = Agent(
    role="Support", goal="Help the customer", backstory="A support agent.",
    llm=llm,                               # your own CrewAI LLM
    skills=decimalai.crewai.skills(),      # the installed folder
    tools=decimalai.crewai.skill_tools(),  # reads a skill's files, runs its scripts
)
task = Task(description="Hello!", expected_output="an answer", agent=agent)
Crew(agents=[agent], tasks=[task]).kickoff()

No DecimalAI package. CrewAI's own loader reads the folder, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/kimlawtech-korean-privacy-terms/SKILL.md

Give it to your agent

from pathlib import Path
from crewai import Agent, Crew, Task

agent = Agent(
    role="Support", goal="Help the customer", backstory="A support agent.",
    llm=llm,                         # your own CrewAI LLM
    skills=[Path(".agents/skills")],
)
task = Task(description="Hello!", expected_output="an answer", agent=agent)
Crew(agents=[agent], tasks=[task]).kickoff()

This gets SKILL.md only. The skill's 14 other files are not included.

Other ways to add it

CrewAI docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[adk]"
decimalai skills add kimlawtech-korean-privacy-terms

Add it to your agent

from decimalai.adk import DecimalAIPlugin, agent_config
from google.adk.agents import LlmAgent
from google.adk.apps import App

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = LlmAgent(
    name="support",          # ADK needs a Python identifier
    model="gemini-3.5-flash",
    instruction=support.instruction,  # your prompt, then the skill list
    tools=[*support.tools],           # your tools, then load_skill
)
# DecimalAIPlugin makes each invocation of runners built from this App one trace.
app = App(name="support", root_agent=agent, plugins=[DecimalAIPlugin()])

Prefer ADK's own loader? SkillToolset(skills=decimalai.adk.skills(), ...) reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

Install

pip install "decimalai[adk]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("kimlawtech-korean-privacy-terms")
if result.exit_code:
    raise SystemExit(result.problems)

from decimalai.adk import DecimalAIPlugin, agent_config
from google.adk.agents import LlmAgent
from google.adk.apps import App

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = LlmAgent(
    name="support",          # ADK needs a Python identifier
    model="gemini-3.5-flash",
    instruction=support.instruction,  # your prompt, then the skill list
    tools=[*support.tools],           # your tools, then load_skill
)
# DecimalAIPlugin makes each invocation of runners built from this App one trace.
app = App(name="support", root_agent=agent, plugins=[DecimalAIPlugin()])

Prefer ADK's own loader? SkillToolset(skills=decimalai.adk.skills(), ...) reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/kimlawtech-korean-privacy-terms/SKILL.md

Give it to your agent

from pathlib import Path
from google.adk.agents import LlmAgent

skill = Path(".agents/skills/kimlawtech-korean-privacy-terms/SKILL.md").read_text()
agent = LlmAgent(
    name="support",
    model="gemini-3.5-flash",
    instruction=lambda context: f"You are a helpful agent.\n\n{skill}",
)

This gets SKILL.md only. The skill's 14 other files are not included.

Other ways to add it

Google ADK docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[pydantic-ai]"
decimalai skills add kimlawtech-korean-privacy-terms

Add it to your agent

from pydantic_ai import Agent
from decimalai.pydantic_ai import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    "openai:gpt-4o-mini",
    name=support.name,
    tools=[],                 # your tools; the capability adds load_skill
    capabilities=[support],   # your prompt, the skill list and load_skill
)
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")

On the Pydantic AI harness, decimalai.pydantic_ai_harness.skills(project) uses its own loader instead.

Install

pip install "decimalai[pydantic-ai]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("kimlawtech-korean-privacy-terms")
if result.exit_code:
    raise SystemExit(result.problems)

from pydantic_ai import Agent
from decimalai.pydantic_ai import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    "openai:gpt-4o-mini",
    name=support.name,
    tools=[],                 # your tools; the capability adds load_skill
    capabilities=[support],   # your prompt, the skill list and load_skill
)
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")

On the Pydantic AI harness, decimalai.pydantic_ai_harness.skills(project) uses its own loader instead.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/kimlawtech-korean-privacy-terms/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/kimlawtech-korean-privacy-terms/SKILL.md").read_text()
agent = Agent("openai:gpt-4o-mini", instructions=f"You are a helpful agent.\n\n{skill}")
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")

This gets SKILL.md only. The skill's 14 other files are not included.

Other ways to add it

Pydantic AI docs

Deep Agents' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" deepagents
decimalai skills add kimlawtech-korean-privacy-terms

Add it to your agent

import decimalai.deepagents
from deepagents import create_deep_agent

agent = create_deep_agent(model=model, **decimalai.deepagents.skills())
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

The default backend reads files but has no shell. To run a skill's scripts, pass skills(backend=LocalShellBackend(...)).

The same install from Python, for a notebook or a setup script. Deep Agents' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" deepagents

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("kimlawtech-korean-privacy-terms")
if result.exit_code:
    raise SystemExit(result.problems)

import decimalai.deepagents
from deepagents import create_deep_agent

agent = create_deep_agent(model=model, **decimalai.deepagents.skills())
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

The default backend reads files but has no shell. To run a skill's scripts, pass skills(backend=LocalShellBackend(...)).

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/kimlawtech-korean-privacy-terms/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/kimlawtech-korean-privacy-terms/SKILL.md").read_text()
agent = create_deep_agent(model=model, system_prompt=f"You are a helpful agent.\n\n{skill}")
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

This gets SKILL.md only. The skill's 14 other files are not included.

Other ways to add it

Deep Agents docs

Its own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" agent-framework
decimalai skills add kimlawtech-korean-privacy-terms

Add it to your agent

import asyncio

from agent_framework import Agent
from decimalai.agent_framework import skills

agent = Agent(client=client, instructions="You are a helpful agent.", context_providers=[skills()])
asyncio.run(agent.run("Hello!"))

It caches skills by default, so restart the process after decimalai skills update.

The same install from Python, for a notebook or a setup script. Its own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" agent-framework

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("kimlawtech-korean-privacy-terms")
if result.exit_code:
    raise SystemExit(result.problems)

import asyncio

from agent_framework import Agent
from decimalai.agent_framework import skills

agent = Agent(client=client, instructions="You are a helpful agent.", context_providers=[skills()])
asyncio.run(agent.run("Hello!"))

It caches skills by default, so restart the process after decimalai skills update.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/kimlawtech-korean-privacy-terms/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/kimlawtech-korean-privacy-terms/SKILL.md").read_text()
agent = Agent(client=client, instructions=f"You are a helpful agent.\n\n{skill}")
asyncio.run(agent.run("Hello!"))

This gets SKILL.md only. The skill's 14 other files are not included.

Other ways to add it

Microsoft Agent Framework docs

Strands' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" strands-agents
decimalai skills add kimlawtech-korean-privacy-terms

Add it to your agent

from decimalai.strands import skills
from strands import Agent
from strands.vended_tools import file_editor, shell

agent = Agent(
    model=model,                # always pass one: the default is Amazon Bedrock
    system_prompt="You are a helpful agent.",
    tools=[file_editor, shell],
    plugins=[skills()],
)
agent("Hello!")

Strands loads an agent's skills once, so build the agent again after decimalai skills update.

The same install from Python, for a notebook or a setup script. Strands' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" strands-agents

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("kimlawtech-korean-privacy-terms")
if result.exit_code:
    raise SystemExit(result.problems)

from decimalai.strands import skills
from strands import Agent
from strands.vended_tools import file_editor, shell

agent = Agent(
    model=model,                # always pass one: the default is Amazon Bedrock
    system_prompt="You are a helpful agent.",
    tools=[file_editor, shell],
    plugins=[skills()],
)
agent("Hello!")

Strands loads an agent's skills once, so build the agent again after decimalai skills update.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/kimlawtech-korean-privacy-terms/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/kimlawtech-korean-privacy-terms/SKILL.md").read_text()
agent = Agent(model=model, system_prompt=f"You are a helpful agent.\n\n{skill}")
agent("Hello!")

This gets SKILL.md only. The skill's 14 other files are not included.

Other ways to add it

Strands docs

Adds every file the skill has, pinned so you can update it. Cursor, Copilot, Cline and Warp read this folder by themselves.

pip install "decimalai>=0.15"
decimalai skills add kimlawtech-korean-privacy-terms

No Python or account. Cursor, Copilot, Cline and Warp read this folder by themselves.

Save it into your project

curl -fsSL --create-dirs -o .agents/skills/kimlawtech-korean-privacy-terms/SKILL.md https://app.decimal.ai/s/kimlawtech-korean-privacy-terms/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/kimlawtech-korean-privacy-terms/SKILL.md

This gets SKILL.md only. The skill's 14 other files are not included.

Other ways to add it

Cursor and other editors docs

Fetch the file and give its text to your model as instructions. No account or package needed.

Get the file

curl -fsSL https://app.decimal.ai/s/kimlawtech-korean-privacy-terms/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/kimlawtech-korean-privacy-terms.json

This gets SKILL.md only. The skill's 14 other files are not included.

Other ways to add it

Other setups docs

You don't need a DecimalAI account.

Version: v1, tested 8/23/2026
Source: kimlawtech/korean-privacy-terms ↗
License: Apache-2.0

Manage it in DecimalAI

Saved prompts and skills, pinned versions, and traces of this skill in your runs. DecimalAI does not run your agent.

Claude Code reads files from your project, so DecimalAI config does not apply there.

On Claude Agent SDK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On OpenAI Agents: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On OpenAI SDK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Anthropic: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Gemini API: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On LangChain: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On CrewAI: set DECIMAL_API_KEY and add decimalai.init(crewai=True) to record runs and skill use. The skill version stays in your repo.

On Google ADK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Pydantic AI: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Deep Agents: set DECIMAL_API_KEY and add decimalai.init(langchain=True) to record runs and skill use. The skill version stays in your repo.

On Microsoft Agent Framework: set DECIMAL_API_KEY and add decimalai.init(otel=True, agent_name="support") to record runs and skill use. The skill version stays in your repo.

On Strands: set DECIMAL_API_KEY and add decimalai.init(otel=True, agent_name="support") to record runs and skill use. The skill version stays in your repo.

Editors read files from your project, so DecimalAI config does not apply there.

Anywhere else: record a use with decimalai.log_skill_activation() inside a trace.

Use this skill

SKILL.md

Korean Privacy & Terms Skill (v4.0 — 하위 스킬 패키지)

하위 스킬 4종

호출 시 번호 메뉴로 안내하고 사용자가 1·2·3·4 중 선택하면 해당 하위 스킬로 직행.

번호	스킬	대상	언어
1	`privacy-kr`	한국 서비스	한국어
2	`privacy-eu`	EU 서비스	영문
3	`privacy-us`	미국 서비스	영문
4	`privacy-global`	한국+EU 병기	한국어+영문

자세한 진입점 동작은 skills/privacy-terms/SKILL.md 참조.

하위 스킬 폴더

skills/privacy-terms/ — 진입점 (번호 메뉴·라우팅)
skills/privacy-kr/ — 한국 PIPA 전용
skills/privacy-eu/ — EU GDPR 전용
skills/privacy-us/ — 미국 CCPA/CPRA + 주요 주법 전용
skills/privacy-global/ — 한국+EU 병기

공유 자산 (legacy, 하위 스킬이 참조):

references/ — 한국법 레퍼런스 10종
jurisdictions/kr-pipa/ — 한국 템플릿 (ko·en)
jurisdictions/eu-gdpr/ — EU GDPR·CRD·DSA 템플릿
assets/components/ — React 컴포넌트
assets/config/ — next.config·mdx-components
scripts/ — interview·render·install 절차
examples/ — 입출력 페어

레거시 설명 (v2.x 단일 스킬 시절)

아래는 v2.x 단일 스킬 동작 설명. v3.0 이후 하위 스킬로 분리됐지만 공유 자산과 법령 레퍼런스는 그대로 사용.

한국 법령에 부합하는 개인정보처리방침과 이용약관, 관련 UI 컴포넌트를 Next.js 프로젝트에 자동 설치한다.

스킬 시작 시 인사 (필수, 맨 처음 출력)

스킬이 호출되자마자 사용자에게 다음 문구를 그대로 출력한 후 인터뷰를 시작한다.

안녕하세요.
한국 법령에 맞는 개인정보처리방침·이용약관을 만들어드릴게요.

반영 기준

  · 개인정보보호위원회 처리방침 작성지침 (2025.4.21)
  · 개정 개인정보보호법 (2026.3 공포, 2026.9.11 시행)
  · 공정거래위원회 전자상거래 표준약관 제10023호

──────────────────────────────────────────

이 스킬은 SpeciAI 에서 만들고 있어요.

SpeciAI는 계약·노동·투자·지재권 같은 법률 리스크를
AI로 빠르게 해결하는 창업자·변호사 커뮤니티예요.

  · 스킬 업데이트 소식 가장 먼저 받기
  · 법률 자동화 팁 공유
  · 변호사 1:1 질의응답
  · 실사용자 피드백 반영

궁금하거나 도움이 필요하시면 들러주세요.
→ https://discord.gg/wQWpEpnBfE

──────────────────────────────────────────

그럼 시작해볼게요. 몇 가지만 여쭤볼게요.

언제 이 스킬을 사용해야 하는가

사용자가 "개인정보처리방침 만들어줘", "이용약관 넣어줘", "쿠키 배너 추가", "/privacy-terms" 등을 요청할 때
한국 사용자 대상 웹서비스에서 법정 공개 문서가 필요한 모든 경우
회원가입 폼에 동의 모달이 필요한 경우

관할법 지원 (v4.0)

🇰🇷 한국 (PIPA + 약관규제법 + 전자상거래법) — references/, jurisdictions/kr-pipa/
🇪🇺 EU (GDPR + ePrivacy + CRD + DSA + DCD + Unfair Terms) — jurisdictions/eu-gdpr/
🇺🇸 미국 (CCPA/CPRA + VCDPA/CPA/CTDPA/UCPA/ICDPA/KCDPA/RIDPA) — jurisdictions/us-ccpa/ (v4.0 신규)
🇯🇵 일본 APPI — 로드맵
🇨🇳 중국 PIPL — 로드맵

인터뷰 Step 0(서비스 성격 스크리닝)에서 자동 결정. 상세는 scripts/interview.md 참조.

법령 근거 (MUST READ)

작업 시작 전 반드시 다음 레퍼런스를 읽는다:

references/law-checklist-2026.md — 개인정보보호법 §30 필수 기재 11개 + 2026.9 시행 신규
references/guideline-2025-04.md — 작성지침 2025.4.21 개정 6대 포인트
references/automated-decision.md — 자동화 결정 안내 (AI 서비스 필수)
references/data-portability.md — 전송요구권 §35조의2
references/ftc-standard-terms.md — 공정위 표준약관 제10023호
references/behavioral-info.md — 행태정보·쿠키 단계별 거부
references/benchmarks.md — 카카오·네이버·토스 구조
references/service-type-matrix.md — 사업 유형별 차이
references/glossary.md — 전문용어 풀어쓰기 사전 (인터뷰·답변 시 필수 참조)
references/design-system-detection.md — 프로젝트 UI 라이브러리·아이콘·CSS 변수 감지

디자인 기본값 철학 (매우 중요)

법률 문서는 "신뢰감 있는 정제된 톤"이 기본이다. 사용자가 Step 10(디자인 확인)에서 명시적으로 변경하지 않는 한 다음을 무조건 적용:

폰트: Pretendard Variable — CDN 자동 추가, font-sans 교체
색상: 흑백 모노크롬 — #0a0a0a / #ffffff / #f5f5f5 기반
MDX 본문 장식 최소화 — 이모지 금지, 볼드는 강조 꼭 필요한 곳만, ## 소섹션은 사용하되 ### 이하 중첩 지양
LabelingCard 기본값: 아이콘 없음(iconSet="none"), 보더 격자, 레이블은 작은 uppercase 스타일
페이지 prose: prose-neutral + 좁은 리딩(max-w-3xl) + 작은 H2 (text-lg)

사용자가 "브랜드 컬러로" 또는 "아이콘 넣어주세요"라고 하면 variant로 전환. 기본은 항상 미니멀.

구체 CSS와 적용 방법: assets/config/layout-snippets.md.

인터뷰 톤·스타일 규칙 (매우 중요)

사용자는 개발자·비법조인이다. 전문용어를 그대로 던지면 안 된다.

모든 질문은 scripts/interview.md 규칙을 따른다
전문용어 등장 시 references/glossary.md의 쉬운 설명으로 풀어쓴다
매 질문마다 왜 묻는지 + 예시 1개 + 선택지 제공
사용자가 "이게 뭐예요?" 물으면 glossary 근거로 2~3줄 답변 후 원래 질문 복귀
공포 유발 표현(과태료 폭탄 등) 금지, "법적으로 필요한 부분이에요" 정도의 톤
"모르시면 넘어가도 됩니다" 옵션 제공

동작 순서

1단계: 프로젝트 감지

지원 환경: Next.js 13~16 (App Router 전용) + Tailwind v3/v4 + Turbopack/Webpack.

디자인 시스템도 같은 단계에서 감지 (references/design-system-detection.md):

UI 라이브러리: shadcn/ui / Chakra / Mantine / MUI / Tailwind 순정 등
아이콘 세트: lucide-react / @heroicons / @tabler / @phosphor-icons
CSS 변수: --radius, --primary, 다크모드 여부
기존 컴포넌트 패턴: rounded-*, shadow-* 빈도 분석
next-themes 존재 여부

감지 결과는 인터뷰 Step 10(디자인 확인)에서 사용자 확인 후 컴포넌트 variant props로 주입.

# Next.js 버전
cat package.json | grep '"next"'

# src/ vs 루트 구조 (매우 중요, 경로 결정)
test -d src/app && echo "src-app" || test -d app && echo "root-app" || echo "unsupported"

# Tailwind 버전
grep -E '"tailwindcss":\s*"\^?4' package.json && echo "tw4" || echo "tw3"

# 번들러
grep -q "turbopack" package.json && echo "turbopack" || echo "webpack"

Pages Router만 있는 경우 스킬 실행 중단. tsconfig.json의 paths["@/*"]를 읽어 컴포넌트 설치 경로를 자동 결정한다. 자세한 절차는 scripts/install.md 참조.

2단계: 의존성 자동 설치

shadcn/ui 미설치 시:

npx shadcn@latest init -d
npx shadcn@latest add dialog button checkbox card separator scroll-area

MDX 미설치 시:

npm install @next/mdx @mdx-js/loader @mdx-js/react @types/mdx remark-gfm
npm install -D @tailwindcss/typography

중요: next.config.{ts,mjs}에 createMDX 래퍼를 추가할 때, Turbopack 환경에서는 remarkPlugins를 문자열 배열로 전달해야 한다 ([["remark-gfm"]]). 함수 참조 시 loader does not have serializable options 에러. 템플릿: assets/config/next.config.ts.tmpl.

3단계 관할별 워크플로우 분기 (v2.3 명시)

Step 0 결과에 따라 인터뷰 범위가 달라진다.

jurisdictions: ["kr-pipa"] (한국만)

Step 1~9 + Step 10·11
Step 9-EU 건너뜀
템플릿: jurisdictions/kr-pipa/*.ko.mdx.tmpl
영문 병기 시 *.en.mdx.tmpl 추가 (PIPA 조문 영문 번역)

jurisdictions: ["eu-gdpr"] (EU만)

Step 1·2·6·9 (서비스·정보·처리위탁·시행일) 유지
Step 3·4·5·7·8 GDPR 재해석 (아래)
Step 9-EU 전부 수집 (Q9E-1~11)
한국 전용 질문(CPO·사업자등록번호·전자상거래법 보유기간·14세 미만 특례) 생략
템플릿: jurisdictions/eu-gdpr/privacy-notice.en.mdx.tmpl, terms-of-service.en.mdx.tmpl

jurisdictions: ["kr-pipa", "eu-gdpr"] (병기)

Step 1·2·6·9 공통 1회만 수집
Step 7 (CPO) 한국 전용으로 수집
Step 8 (14세 미만) 한국·EU 각각 기준 수집 — 16세로 통일 권장
Step 9-EU 전부 수집
한국·EU 두 세트 문서 동시 생성
- /privacy (한국어 PIPA)
- /eu/privacy (영문 GDPR)
- /terms (한국어 KFTC)
- /eu/terms (영문 CRD·DSA)

Step 4·5·7의 GDPR 재해석

EU 단독/병기 시 기존 Step 답을 GDPR 카테고리로 재매핑한다. 사용자에게 다시 묻지 않고 Claude가 자동 변환 후 Step 9-EU에서 확인 받는다.

한국 질문	GDPR 대응
Step 4 처리 목적	Art. 6 Legal Basis로 매핑 (Q9E-4)
Step 5 제3자 제공	Art. 13(1)(e) Recipients (Q9E-8)
Step 6 처리위탁	Art. 28 Processors + 국제 이전 (Q9E-7)
Step 7 CPO	GDPR DPO 겸임 또는 별도 (Q9E-2)

3단계: 사용자 인터뷰 — 성격 스크리닝 먼저

v2.1부터 인터뷰 첫 단계는 "서비스 성격 스크리닝"이다. 세부 질문 전에 다음을 먼저 확정:

Step 0-A: 대상 사용자 (한국만 / 해외 위주 / 양쪽 글로벌)
Step 0-B: (글로벌 선택 시) 해외 주력 지역 (EU / 미국 / 아시아 / 전세계)
Step 0-C: 운영 주체 소재지 (한국 / 해외)

이 3개 답을 바탕으로 Claude가 자동 결정:

jurisdictions: ["kr-pipa"] / ["eu-gdpr"] / ["kr-pipa", "eu-gdpr"]
outputLocale: ko / en / both
이후 세부 질문 범위 (EU 단독이면 CPO·전자상거래법 보유기간 안 물음)

사용자에게 결정 요약을 보여주고 확인받은 뒤 Step 1~9 진행.

한국만 선택 → Step 1~~9 한국 버전 (기존 v1) EU만 선택 → Step 1~~9 EU 버전 (DPO, Legal Basis, 국제 이전 등) 병기 선택 → 공통 질문 1회 + 관할별 고유 질문 추가

scripts/interview.md Step 0 상세 로직 참조. 한 번에 1~2문항씩. 필수 정보 수집 전에는 생성 금지.

3.3단계: 디자인 스타일 확인 (Step 10)

scripts/interview.md Step 10 참조. 1단계에서 감지한 결과를 사용자에게 요약 제시하고:

"이대로" → 감지값 그대로 variant 적용
"바꾸고 싶어요" → 5개 세부 질문 (모달 · 쿠키 배너 · 모서리 · 아이콘 · 컬러)

최종 variant 객체 (scripts/render.md의 치환 Step에 전달):

styleVariant:
  modal: default       # default | compact | large | minimal
  cookieBanner: bottom-bar  # bottom-bar | floating | top-bar | center-modal
  iconSet: lucide      # lucide | none
  labelingLayout: grid # grid | list
  labelingDensity: comfortable  # compact | comfortable

3.5단계: 템플릿 치환 (Claude 직접 수행)

치환 엔진을 별도로 사용하지 않는다. Claude가 scripts/render.md의 프로토콜을 따라 직접 수행.

핵심 규칙:

{{변수}} → 인터뷰 수집 값
{{#if 조건}}...{{/if}} → 조건 평가 후 블록 제거 or 유지 (태그는 반드시 삭제)
{{#each 배열}}...{{/each}} → 배열 원소 수만큼 블록 복제, 표 헤더는 1회만
collectedItemsSummary, purposesSummary, thirdPartySummary, processorSummary 같은 파생 변수는 Claude가 직접 계산
Write 직전 반드시 검증: {{ 패턴 0건, 법정 11개 항목 포함

상세 절차와 예시는 scripts/render.md 참조.

3.7단계: 페이지·모달에 variant 주입

컴포넌트 파일을 복사할 때 기본 variant를 Step 10 결과로 박아넣기. 예:

// src/app/privacy/page.tsx
<LabelingCard layout="grid" density="comfortable" iconSet="lucide" />

// src/app/layout.tsx (사용자 안내용 예시)
<CookieBanner variant="bottom-bar" iconSet="lucide" />

// 회원가입 페이지
<ConsentModal variant="default" size="md" iconSet="lucide" />

사용자가 "감지된 것 그대로"라고 답하면 props 기본값 그대로 두고, 커스터마이즈했다면 해당 값으로 박는다.

4단계: 파일 생성

경로는 1단계에서 감지한 src-app / root-app 구조에 따라 분기. 아래는 src-app 기준.

공통 (outputLocale 무관):

src/mdx-components.tsx — App Router MDX 렌더링 필수
src/app/privacy/page.tsx — 처리방침 페이지 라우트
src/app/terms/page.tsx — 이용약관 페이지 라우트
src/components/legal/ConsentModal.tsx
src/components/legal/CookieBanner.tsx
src/components/legal/LabelingCard.tsx

outputLocale: ko (기본):

src/content/legal/privacy-policy.mdx — 한국어
src/content/legal/terms-of-service.mdx — 한국어
페이지에 locale="ko" props

outputLocale: en:

src/content/legal/privacy-policy.mdx — 영문 (privacy-policy.en.mdx.tmpl 치환)
src/content/legal/terms-of-service.mdx — 영문
페이지·컴포넌트에 locale="en" props

outputLocale: both (한/영 병기):

src/content/legal/privacy-policy.mdx — 한국어
src/content/legal/terms-of-service.mdx — 한국어
src/content/legal/privacy-policy.en.mdx — 영문
src/content/legal/terms-of-service.en.mdx — 영문
src/app/en/privacy/page.tsx — 영문 라우트
src/app/en/terms/page.tsx — 영문 라우트
Footer에 언어 전환 링크 제공 안내

(아이콘은 lucide-react 사용, 별도 SVG 번들 없음)

5단계: 필수 검증 (생성 후)

다음 체크리스트를 반드시 만족해야 한다. 하나라도 누락 시 경고 후 수정.

개인정보처리방침 필수 11항목 (개인정보보호법 §30):

2025.4 지침 반영 추가 항목:

전송요구권 행사 방법 (2025.3.13 시행)
자동화 결정 기준·절차·방식 (AI 서비스 시)
행태정보 처리 및 거부권 (쿠키 단계별 차단법)
고충처리 부서 연락처

2026.9 시행 신규:

사업주/대표자 책임 명시 (§30조의3)
유출 통지 대상 확대 반영

6단계: 면책 주석 필수 삽입

모든 생성 파일 상단에 다음 주석 삽입:

{/* 본 초안은 2025.4.21 개인정보 처리방침 작성지침 및 2026.3.10 공포 개정 개인정보보호법을 반영하였으나, 개별 서비스 특성에 따른 법률 검토가 필수입니다. 과징금이 매출액 10%로 상향되었으므로 배포 전 반드시 법률자문을 받으세요. */}

금지 사항

법정 필수 11개 항목 중 하나라도 누락 금지
"등"으로 뭉뚱그린 표현 금지 (작성지침 위반)
면책 주석 제거 금지
사용자 확인 없이 실제 회사명·책임자명 추측 금지
14세 미만 대상 서비스에 성인용 방침 그대로 사용 금지

서비스 유형별 분기

references/service-type-matrix.md 참조:

SaaS: 결제정보·API 토큰·로그 처리
쇼핑몰: 전자상거래 표준약관 10023호 기반 + 청약철회
블로그/개인: 최소 필수 항목만

출력 포맷 예시

생성 완료 후 사용자에게 보고:

[생성 완료]
- content/legal/privacy-policy.mdx
- content/legal/terms-of-service.mdx
- app/privacy/page.tsx
- app/terms/page.tsx
- components/legal/ConsentModal.tsx
- components/legal/CookieBanner.tsx
- components/legal/LabelingCard.tsx

[검증]
- 법정 11개 항목: OK
- 2025.4 지침 반영: OK
- 2026.9 신규 조항: OK

[다음 단계]
1. app/layout.tsx에 <CookieBanner /> 삽입
2. 회원가입 폼에 <ConsentModal /> 연결
3. Footer에 /privacy, /terms 링크 추가
4. 법률 검토 권장

[경고]
본 초안은 참고용입니다. 실서비스 배포 전 변호사 검토를 받으세요.
과징금 매출액 10% (2026.9.11 시행).

[커뮤니티]
SpeciAI 디스코드 — 한국 법률 AI 허브
계약·노동·투자·지재권을 AI로 해결하는 창업자·변호사 커뮤니티
https://discord.gg/wQWpEpnBfE

About this skill

Automatic

Legal & Contracts pack

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/3/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

kimlawtech / korean-privacy-terms

SKILL.md

View on GitHub ↗

License Apache-2.0Imported 8/3/2026Version v1Bundled 14 files · scripts

Illustrative Want to see what kimlawtech/korean-privacy-terms would put in front of your model? Preview the rendered body and check its trigger phrases — no LLM call, no signup.

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kimtth/add-new-entry-from-temp-mdWorkflow and tools for adding new entries from temp.md to the section files. Includes legend format, section reference, code tools, and common pitfalls. USE FOR: Adding new resources to the knowledge base. DO NOT USE FOR: Editing existing entries or restructuring sections.+59 pts pass-rate lift

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Korean Privacy & Terms Skill (v4.0 — 하위 스킬 패키지)

하위 스킬 4종

하위 스킬 폴더

레거시 설명 (v2.x 단일 스킬 시절)

스킬 시작 시 인사 (필수, 맨 처음 출력)

언제 이 스킬을 사용해야 하는가

관할법 지원 (v4.0)

법령 근거 (MUST READ)

디자인 기본값 철학 (매우 중요)

인터뷰 톤·스타일 규칙 (매우 중요)

동작 순서

1단계: 프로젝트 감지

2단계: 의존성 자동 설치

3단계 관할별 워크플로우 분기 (v2.3 명시)

Step 4·5·7의 GDPR 재해석

3단계: 사용자 인터뷰 — 성격 스크리닝 먼저

3.3단계: 디자인 스타일 확인 (Step 10)

3.5단계: 템플릿 치환 (Claude 직접 수행)

3.7단계: 페이지·모달에 variant 주입

4단계: 파일 생성

5단계: 필수 검증 (생성 후)

6단계: 면책 주석 필수 삽입

금지 사항

서비스 유형별 분기

출력 포맷 예시

SkillSafety

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